Feature-based multi-resolution registration of immunostained serial sections

•We non-rigidly register immunohistological serial sections of human specimen.•Using feature detection and matching we iteratively compute non-rigid deformations.•Vascular networks in spleen and bone marrow are shown on a level not possible before.•A quantitative evaluation of our method shows its e...

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Veröffentlicht in:Medical image analysis 2017-01, Vol.35, p.288-302
Hauptverfasser: Lobachev, Oleg, Ulrich, Christine, Steiniger, Birte S., Wilhelmi, Verena, Stachniss, Vitus, Guthe, Michael
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Sprache:eng
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Zusammenfassung:•We non-rigidly register immunohistological serial sections of human specimen.•Using feature detection and matching we iteratively compute non-rigid deformations.•Vascular networks in spleen and bone marrow are shown on a level not possible before.•A quantitative evaluation of our method shows its efficiency. [Display omitted] The form and exact function of the blood vessel network in some human organs, like spleen and bone marrow, are still open research questions in medicine. In this paper, we propose a method to register the immunohistological stainings of serial sections of spleen and bone marrow specimens to enable the visualization and visual inspection of blood vessels. As these vary much in caliber, from mesoscopic (millimeter-range) to microscopic (few micrometers, comparable to a single erythrocyte), we need to utilize a multi-resolution approach. Our method is fully automatic; it is based on feature detection and sparse matching. We utilize a rigid alignment and then a non-rigid deformation, iteratively dealing with increasingly smaller features. Our tool pipeline can already deal with series of complete scans at extremely high resolution, up to 620 megapixels. The improvement presented increases the range of represented details up to smallest capillaries. This paper provides details on the multi-resolution non-rigid registration approach we use. Our application is novel in the way the alignment and subsequent deformations are computed (using features, i.e. “sparse”). The deformations are based on all images in the stack (“global”). We also present volume renderings and a 3D reconstruction of the vascular network in human spleen and bone marrow on a level not possible before. Our registration makes easy tracking of even smallest blood vessels possible, thus granting experts a better comprehension. A quantitative evaluation of our method and related state of the art approaches with seven different quality measures shows the efficiency of our method. We also provide z-profiles and enlarged volume renderings from three different registrations for visual inspection.
ISSN:1361-8415
1361-8423
DOI:10.1016/j.media.2016.07.010